Queries with OpenAI: Translate Natural Text to SQL

Ever wanted to seamlessly translate natural language into actionable insights from your data? This Guided Project was created to help learners develop the skillset necessary to utilize OpenAI GPT to generate complex SQL queries from natural language prompts to elicit insights against a real sql database. In this project-based course, spanning 2-hours, you will load data from a CSV file and convert it to a local Pandas dataframe. You will create an SQL-like table definition prompt based on the dataframe. You will use this as well as a user query to build a comprehensive GPT prompt to elicit a real SQL query which we will then use to interact with our data. By the end of this project you will have built a powerful tool that can convert a natural language questions into SQL queries and interactively pull insights from a real-world dataset. In order to be successful with this project you should have some experience in Python programming, working with GPT or GPT API, a working understanding of SQL and a credit card for tokens to use with OpenAI API.

• Project Overview
• This is an intermediate-level project-based course which should take approximately 2 hours to finish. You will load data from a CSV file and convert it to a local Pandas dataframe. You will create an SQL-like table definition prompt based on the dataframe. Use this, as well as a user query, to build a comprehensive GPT prompt to elicit a real SQL query which you will then use to interact with the data. By the end of this project, you will have built a powerful tool that can convert a natural language question into SQL queries and interactively pull insights from a real-world dataset.